Qualitative research Qualitative research is a method of scientific observation to collect non-numerical data. This type of research "refers to the meaning, definition of concepts, characteristics, metaphors, symbols, and descriptions of things" and not to their "number or size". Qualitative research approaches are used in many academic disciplines, especially focusing on the human element of the social and natural sciences; in a less academic context, areas of application include qualitative market research, business, nonprofit service demonstrations, and journalism.
As a field of study, qualitative approaches include concepts and research methods from various predefined academic areas. The objectives of a qualitative research project may vary with disciplinary background, such as a psychologist seeking an in-depth understanding of human behavior and the reasons that govern such behavior for example. The best qualitative method to examine the many questions of why and how about human experience, in making decisions for example (not just what ,
In the conventional view of statisticians, qualitative methods only produce explanations of the particular cases being studied (for example, as part of the ethnography of newly implemented government programs), other more general conclusions are considered temporary propositions (informed statements). Quantitative methods can be used to seek further mathematical support for the research hypothesis.
Conversely, a qualitative researcher may argue that an understanding of a phenomenon or situation or event, derives from exploring the totality of the situation (eg, phenomenology, symbolic interactionism), often with access to large amounts of "hard data" of nonnumerical forms. This may begin as a grounded theory approach with researchers who have no previous understanding of the phenomenon; or research can begin with a proposition and proceed with 'scientific and empirical ways' during the research process (eg, Bogdan & Taylor, 1990).
The most popular qualitative research method is the case study (Stake 1995, Yin 1989), which examines in depth 'purposive samples' to better understand a phenomenon (eg, support for families; Racino, 1999); Case study methods exemplify the qualitative researchers' preferences for depth, detail, and context, often working with smaller and more focused samples, compared to large samples of major interest to statistical researchers seeking common law.
The qualitative method is an integral component of the five angles of analysis fostered by the data percolation methodology. These methods can be used in conjunction with quantitative methods, scientific or literary reviews of literature, interviews with experts, and computer simulations, as part of a multimetode attitude for data collection and analysis (called Triangulation).
To help navigate the heterogeneous landscape of qualitative research, one can further consider the qualitative inquiry in terms of 'means' and 'orientation' (Pernecky, 2016). In particular, one can argue that qualitative researchers often reject the natural science model of truth, prefer research processes and procedures that generate hypotheses (more than hypothesis testing models), oriented to the investigation of meaning (s) rather than behavior, and prefer data in forms of words and images, ideally obtained naturally (eg deep observations as opposed to experiments).
Video Qualitative research
History
Babbie notes that qualitative research is "very old and very new." Babbie, a sociologist, documented that qualitative methods had been used for several centuries, but anthropologists brought qualitative field research methods to the surface through the observation of the 19th century preliterate society.
Robert Bogdan in his advanced course on qualitative research tracing the history of field development, and their particular relevance to disability and including the work of his colleague Robert Edgerton and founder of participant observation, Howard S. Becker. As Robert Bogdan and Sari Biklen explain in their educational texts, "qualitative research historians never, for example, include Freud or Piaget as developers of a qualitative approach, but both rely on case studies, observations and in-depth interviews."
In the early 1900s, some researchers rejected positivism, the theoretical notion that there is an objective world that can collect data from and "verify" this data through empiricism. These researchers adhere to a qualitative research paradigm, trying to make qualitative research "strict" as quantitative research and creating a variety of methods for qualitative research. Such developments are needed when qualitative researchers win national center awards, in collaboration with their research colleagues at universities and other departments; and university administration funded Ph.D.s in both arenas through the next decade. Much of the theoretical constructs involve a process of qualitative analysis and understanding, and the construction of these concepts (eg, Wolfensberger's social role theories).
In the 1970s and 1980s, the rise of computer-aided in various qualitative analyzes, some journals with qualitative focus emerged, and postpositivism gained recognition at the academy. In the late 1980s, identity problems arose, including race, class, gender, and discourse communities, leading to more reflexive research and writing. Throughout the 1990s, the concept of passive observers/researchers was rejected, and qualitative research became more participatory and activist-oriented with support from federal branches, such as the National Institute for Research and Disability Rehabilitation (NIDRR) of the US Department. Education (eg, Research Center for Rehabilitation and Training for Families and Community Life, 1990). Also, during this time, researchers began using a mixed-method approach, indicating a shift in the thinking of qualitative and quantitative methods as being intrinsically incompatible. However, this history is not apolitical, as it has led to "evidence" politics (eg, evidence-based practice in health and human services) and what can be considered "scientific" research in scholarship, ongoing debate at the Academy.
Maps Qualitative research
Data collection, analysis and design of field research
Qualitative researchers face many options for techniques to generate data ranging from the development and practice of abandoned theories, narratives, narratives, transcripts, classical ethnographies, country or government studies, research and service demonstrations, focus groups, case studies, participant observation, a qualitative review of statistics to predict future events, or shadowing, among many others. Qualitative methods are used in various methodological approaches, such as action studies that have a sociological basis, or network-actors theory.
Interviews (structured, semi-structured or unstructured) are common sources of data on the quality/interest categories. Other sources include focus groups, observations (without a predetermined theory such as statistical theory in mind for example), reflective field notes, text, images, photographs and other images, interactions and practices captured on audio or video recordings, public (eg official) personal documents, historic items, and websites and social media.
To analyze qualitative data, researchers sought the meaning of all available data. Data can be categorized and sorted into patterns (ie, patterns or thematic analysis) as the main basis for organizing and reporting study findings (eg, activities at home, interaction with government). Qualitative researchers, often associated with the field of education, usually rely on the following methods to collect information: Participant Observation, Non-attendance Observation, Field Records, Reflexive Journals, Structured Interviews, Semi-Structured Interviews, Unstructured Interviews, and Analysis. documents and materials .
The ways of participating and observing may vary from setting to setting as exemplified by Helen Schwartzman's primary of Ethnography in Organization (1993). or Anne Copeland and Kathleen White's "Studying Families" (1991). Participant observation is a reflexive learning strategy, not a single observing method. and has been described as a continuum between participation and observation. In participant observations, researchers usually become members of a culture, group, or setting, and adopt a role to adapt to that arrangement. Thus, the goal is for researchers to gain a closer insight into cultural practice, motivation, and emotion. It is said that the ability of researchers to understand cultural experiences can be hampered if they observe without participating.
The data obtained is efficient (text from thousands of pages long) to a definite theme or pattern, or representation of a theory or issue or systemic approach. This step in further theoretical analysis or analytical techniques of data is done (eg, gender analysis can be done, comparative policy analysis can be developed). An alternate research hypothesis is generated that ultimately provides the basis of research statements to continue the work in the field.
Some typical qualitative methods are the use of focus groups and key informant interviews, the latter often identified through sophisticated and sometimes elitist, snowball techniques. Focus group techniques (eg, Morgan, 1988) involve moderators facilitating small group discussions between selected individuals on a particular topic, by recording video and recorded data, and useful in a coordinated research approach that studies phenomena in different ways in different environments. with different stakeholders often excluded from traditional processes. This method is very popular in market research and testing new initiatives with users/workers.
Research should then be "written" into reports, book chapters, journal papers, theses or dissertations, using descriptions, excerpts from participants, charts and tables to demonstrate the confidence of the research findings.
In qualitative research, the idea of ​​recursivity is expressed in terms of the nature of the research procedure, which can be contrasted with the form of experimental research design. From an experimental perspective, the main stages of the study (data collection, data analysis, discussion of data in literary contexts, and drawing conclusions) should be done once (or at most several times) in the study. However, in qualitative research, these four steps can be repeated over and over until one or more specific stop conditions are met, reflecting non-static attitudes toward the planning and design of research activities. An example of this dynamic may be when qualitative researchers unexpectedly alter their research or design focus in the middle through a research study, based on their interim analysis of data 1, and then make unplanned changes based on a second interim data analysis; this would be a terrible thing to do from the perspective of experimental studies (pre-determined) on the same thing. Qualitative researchers will argue that their recursiveness in developing relevant evidence and reasoning, allowing researchers to be more open to unexpected results, more open to the potential for new constructions, and possibly integrating them with explanations developed continuously throughout the study.
Custom use of qualitative research
Qualitative methods are often part of the survey methodology, including telephone surveys and consumer satisfaction surveys.
In the area of ​​household study, the subject of much debate is whether the interview should be done individually or collectively (eg as a couple interview).
One of the traditional and specific forms of qualitative research is called cognitive tests or trials used in the development of quantitative survey items. Survey items were piloted on the study participants to test the reliability and validity of the items. This approach is similar to psychological testing using intelligence tests such as WAIS (Wechsler Adult Intelligence Survey) in which the interviewer noted "qualitative" (ie clinical observation) during the testing process. Qualitative research is often useful in sociological lenses. Although often overlooked, qualitative research is very useful for sociological studies that can explain the intricacies of community function and human interaction.
There are different research approaches, or research designs, which qualitative researchers use. In academic social sciences, the most commonly used qualitative research approach includes the following:
- Basic/generic/pragmatic qualitative research, involving the use of an eclectic approach taken to best suit the research questions at hand. This is often called the mixed method approach.
- Ethnographic Research. Examples of applied ethnographic research are the study of specific cultures and their understanding of the role of specific diseases within their cultural framework.
- Grounded Theory is a type of inductive, grounded or "grounded" study in the observation or data from which it was developed; using a variety of data sources, including quantitative data, notes reviews, interviews, observations, and surveys.
- Phenomenology describes the "subjective reality" of an event, as perceived by the study population; it is the study of a phenomenon.
- Philosophical research is conducted by field experts within the boundaries of a particular field of study or profession, the best qualified individuals in each field of study to use intellectual analysis, to clarify definitions, identify ethics, or make judgment scores on issues in their field of life they.
- Critical Social Research, is used by researchers to understand how people communicate and develop symbolic meaning.
- Ethical Inquiry, intellectual analysis of ethical issues. This includes ethical studies related to obligations, rights, duties, right and wrong, options etc.
- Social Sciences and Government Research to understand social services, government operations, and recommendations (or not) on future developments and programs, including whether the government should be involved or not.
- Research Activists aimed at improving the views of the less fortunate or "underdog" to stand out to the elite or master class, the latter of which often controls public views or positions.
- Basic Research, testing the foundations for science, analyzing beliefs, and developing ways to determine how the knowledge base should change because of new information.
- Historical research allows one to discuss past and present events in the context of the current conditions, and enable one to reflect and provide possible answers to current problems and problems. Historical research helps us answer such questions as: Where do we come from, where are we, who we are now and where we are going?
- Visual Ethnography. It uses visual data collection methods, including photos, sounds, photo elicitation, collages, drawings, and mapping. These techniques have been used extensively as participative qualitative techniques and make familiar strangers.
- Autotnography, self study, is a qualitative research method in which researchers use their personal experiences to solve problems.
Data analysis
Interpretive techniques
As a form of qualitative inquiry, students of interpretive questions often disagree with the idea of ​​observation or theoretical knowledge. While this crucial philosophical embodiment is also held by researchers in other fields, interpreters are often the most aggressive in taking this philosophical realization to its logical conclusion. For example, an interpretive researcher may believe in the existence of objective reality 'out there', but argues that our social and educational realities act on the basis of never allowing a human subject to direct access to the 'out there' reality in reality views shared by the constructivist philosophy).
For researchers outside the field of qualitative research, the most common qualitative data analysis is often regarded as an observer's impression. That is, expert observers or observers examine the data, interpret it through the formation of impressions and report their impressions in a structured and sometimes quantitative form.
Encoding
In general, coding refers to the act of associating meaningful ideas with interesting data. In the context of qualitative research, the interpretive aspects of the coding process are often explicitly acknowledged, articulated, and celebrated; produce certain words or short phrases that are believed to be a useful abstraction of data.
As an act of making sense, most coding requires qualitative analysts to read the data and demo segments within it, which can be done at different times and multiple times during the data analysis process. Each segment is labeled with 'code' - usually a short word or phrase that shows how the related data segment informs the research objectives. In contrast to more quantitative forms of coding, mathematical ideas and forms are usually less developed in 'pure' qualitative data analysis. When the coding is complete, the analyst can prepare the report through the mix: summarize the prevalence of the code, discuss the similarities and differences in related code across different sources/different contexts, or compare the relationships between one or more codes.
Some highly structured qualitative data (eg, open responses from surveys or strictly defined interview questions) are usually encoded with minimal additional data segmentation. Quantitative analysis based on the code of statistical theory is usually the analytical step of the capstone for this type of qualitative data. The common form of coding is open coding, while other more structured techniques such as axial encoding or integration have also been described and articulated (Strauss & Corbin, 1990). Because qualitative analysis is often more inductive than the nature of hypothesis testing of most quantitative research, the existing 'theoretical sensitivity' (ie, familiarity with existing theories in the field) of the analyst becomes a more urgent concern in generating acceptable analysis.
The analysis of contemporary qualitative data is often supported by computer programs (called Computer Assisted Qualitative Data Analysis Software) used with or without detailed coding and hand-labeling over the last few decades. These programs do not replace the interpretive nature of the coding, but rather are intended to improve the efficiency of analysts in implementing, retrieving, and storing code generated from reading data. Many programs improve efficiency in code editing and revision, allowing more effective division of labor, peer review, recursive data collection, and large data collection analysis.
General Qualitative Data Analysis Software includes:
- MAXQDA (mixed method)
- QDA MINER
- ATLAS.ti
- Dedoose (mixed method)
- NVivo
A frequent criticism of the quantitative coding approach contradicts the transformation of qualitative data into predictive data structures (named), backed by 'objective nature'; diversity, wealth, and individual characteristics of qualitative data are debated to be largely omitted from such data encoding processes, rendering the original collection of qualitative data somewhat meaningless.
To defend themselves from criticism of too much subjective variability in the categories and relationships identified from the data, qualitative analysts respond by thoroughly articulating their definition of code and linking the codes well to the underlying data, thereby retaining some of the wealth there may not be only a list of codes, while satisfying the need for repetitive procedures held by experimentally oriented researchers.
Recursive abstraction
As defined by Leshan 2012, this is a qualitative data analysis method in which the qualitative dataset is analyzed without coding. The general method here is a recursive abstraction, in which the data set is summarized; Therefore the summary is outlined in summary and so on. The end result is a more concise summary that will be difficult to accurately distinguish without previous distillation.
A frequent criticism of recursive abstraction is that the final conclusions are deleted several times from the underlying data. While it is true that a poor initial summary will result in an inaccurate final report, qualitative analysts can respond to this criticism. They do so, like those who use the coding method, by documenting the reasons behind each summary step, citing examples of data where statements are inserted and where statements are excluded from intermediate summaries.
Coding and "thinking"
Some data analysis techniques, often referred to as tedious and difficult research jobs that are similar to field notes, depend on the use of computers to scan and reduce a large set of qualitative data. At the most basic level, numerical coding depends on the calculation of words, phrases, or accidental tokens in the data; Other similar techniques are phrase analysis and exchange in conversation analysis. Often referred to as content analysis, the basic structural building blocks for conceptual analysis, this technique uses a mixed methodology to disassemble both small and large corpus. Content analysis is often used in sociology to explore relationships, such as changes in racial perception over time (Morning 2008), or temporal contractor lifestyle (Evans, et al., 2004). Content analysis techniques thus help provide wider output for larger and more accurate conceptual analysis.
Mechanical engineering is perfect for several scenarios. One such scenario is for datasets that are too large to be effectively analyzed by humans, or where their analysis would cost a relative cost to the value of the information it contains. Another scenario is when the primary value of the dataset is the extent to which it contains a "red flag" (eg, looking for reports of certain side effects in a patient's long dataset dataset in clinical trials) or "green flag" (eg, looking for your brand name in the review positive from market products). Many researchers will consider this procedure on their data set to misuse their collection and data collection purposes.
A frequent criticism of mechanical techniques is the absence of a human translator; computer analysis was relatively recent after arriving in the late 1980s into the university sector. And while the experts of this method are able to write sophisticated software to imitate some human decisions, most of the "analysis" is still inhumane. Analysts respond by proving the value of their method is relatively good a) recruiting and training human teams to analyze data or b) by letting data untouched, leaving undisclosed nuggets undiscovered; almost all coding schemes indicate a possible study for further research.
The data set and its analysis should also be written, reviewed by other researchers, circulated for comment, and completed for public review. Numeric coding should be available in published articles, if the methodology and findings should be compared across the study studies in traditional literature reviews and recommendations format.
Different qualitative paradigms
Contemporary qualitative research has been conducted using a large number of paradigms that affect the conceptual and metatheoretical concerns of legitimacy, control, data analysis, ontology, and epistemology, among others. Qualitative research conducted in the twenty-first century is characterized by different changes toward more interpretive, postmodern, and critical practices. Guba and Lincoln (2005) identify five main paradigms of contemporary qualitative research: positivism, postpositivism, critical theory, constructivism, and participative/cooperative paradigms. Each of the paradigms listed by Guba and Lincoln is characterized by axiomatic differences in axiology, intended action/research impact, process control/research results, relationships with the basics of truth and knowledge, validity and trust (see below), textual representation and the voice of researchers and research participants, and conformity with other paradigms. In particular, komensurability involves the extent to which concerns of 2 paradigms for example, "can be reassembled to each other in a way that makes the simultaneous practice of both possibilities". Positivist and positivist paradigms share a comparable assumption, but most can not be compared to a critical, constructivist, participatory research and knowledge paradigm. Likewise, critical, constructivist, and participatory paradigms can be likened to certain issues (eg, intended action and textual representation of the research).
Qualitative research in the 2000s is also characterized by concern for everyday categorization and ordinary storytellers. This "narrative turnaround" produces enormous literature because researchers present drunken concepts and perspectives that are primarily concerned with the practice of narrative, centered on circumstances and communicative acts of storytelling. Catherine Riessman (1993) and Gubrium and Holstein (2009) provide an analytic strategy, and Holstein and Gubrium (2012) present various approaches in the most comprehensive comprehensive texts. More recent developments in narrative practice have increasingly raised the institutional institutionalization of such practices (see Gubrium and Holstein 2000).
Trust
The main problem in qualitative research is trust (also known as credibility, or in quantitative studies, validity). There are many ways to build trust, including: member checks, interview correctness, peer debriefing, long-term engagement, case negatives analysis, auditability, confirmability, bracketing, and balance. Most of these methods are described in Lincoln and Guba (1985). As exemplified by Preston Teeter and Jorgen Sandberg researchers, data triangulation and examples of interview accounts are the two most commonly used methods of building trust in qualitative studies. Dependency is equivalent to the idea of ​​reliability in quantitative methods and the extent to which two or more people tend to come to the same conclusion by examining the same evidence. Again, Lincoln and Guba (1985) are prominent references.
Qualitative research journal
In the late 1970s many leading journals began to publish qualitative research articles and several emerging journals that only published qualitative research and articles on qualitative research methods. In the 1980s and 1990s, new qualitative research journals became more multidisciplinary in focus moving beyond the roots of the discipline of anthropology, sociology, and traditional philosophy of qualitative research. In the late 1980s to the 1990s, early academic articles emerged beginning with the transformation of institutional studies (eg, Taylor's "Let them eat program") for community studies, community services and community life reviewed and cited in professional journals. These studies range from highly controversial concerns involving capital punishment and disability (Bogdan, 1995) to family efforts with service providers (O'Connor, 1995) to the government division governing families by "coming to take" children away (Taylor, 1995).
Qualitative research in psychology
Wilhelm Wundt, founder of scientific psychology, was one of the first psychologists to conduct qualitative research. Early examples of qualitative research were published in 1900 to 1920, in his 10-volume study, VÃÆ'¶lkerpsychologie (translated into: Social Psychology). Wundt advocated a strong relationship between psychology and philosophy. He believes that there is a gap between psychology and quantitative research that can only be filled by conducting qualitative research. Qualitative research goes into aspects of human life that can not be adequately covered by quantitative research; aspects such as culture, expression, belief, morality and imagination.
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